Epilepsy is a disorder of the brain characterized by chronic, recurring seizures. Seizures can be a result of uncontrolled discharges of electrical activity in the brain. A seizure typically manifests as sudden, involuntary, disruptive, and often destructive sensory, motor, and cognitive phenomena.
One tool for evaluating the physiological states of the brain is the electroencephalogram (EEG). The standard for analysis and interpretation of the EEG is visual inspection of the graphic tracing of the EEG by a trained clinical electroencephalographer. It can be difficult to predict a seizure onset by visual analysis of the EEG. Traditional signal processing techniques yield little practical information about the EEG signal.
Recent multi-center clinical studies showed evidence of premonitory symptoms in 6.2% of 500 patients with epilepsy (See “Seizure anticipation by patients with focal and generalized epilepsy: a multicentre assessment of premonitory symptoms” by Schulze-Bonhage et al., 2006). Another interview-based study found that 50% of 562 patients felt “auras” before seizures (See “Hungarian multicentre epidemiologic study of the warning and initial symptoms of epileptic seizures” by Rajna et al., 1997). Such clinical observations give an incentive to search for premonitory changes on EEG recordings from the brain.
Current seizure prediction approaches can be summarized into, e.g., (1) extracting measurements from EEG over time, and (2) classifying them into a preictal or interictal state. The ictal and postictal states can be discarded from the classification, because the task is not to detect undergoing seizures, but eventually to warn the patient about future seizures, so that the patient, the clinician and/or an implanted device can act accordingly.
Certain techniques provide, with less than desirable accuracy, seizure detection during the very early stages of a seizure discharge in the EEG (e.g., a few seconds after the initial discharge). Techniques capable of providing true seizure prediction and/or warning would likely be of high importance, not only to those afflicted with seizure disorders, but also to those members of the medical community who are committed to providing care and effective treatment for those who suffer from epileptic seizure related conditions.
Thus, it can be desirable to provide a method and apparatus for predicting seizures with such accuracy that the activity of the brain can be monitored so that preventative actions through application of intervention measures to abort or modulate the seizure prior to clinical onset.